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Instale o docker no seu computador (https://www.docker.com/products/docker-desktop/)
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Instalação do DBT via source (https://docs.getdbt.com/docs/core/source-install) 2.1 Criar uma pasta chamada dbt-project 2.2 Vamos criar um ambiente virtual chamado dbt-env (python -m venv dbt-env) 2.3 Ativar o dbt-env (source dbt-env/Scripts/activate) 2.4 Clonar o repo do DBT na pasta (git clone https://github.com/dbt-labs/dbt-core.git) 2.5 Navegar até a pasta DBT-CORE (cd dbt-core) 2.6 Instalar os requirements (pip install -r requirements.txt)
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Para iniciar o DBT basta digitar dbt init [OPTIONS] [project-name] (https://docs.getdbt.com/reference/commands/init)
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Instalação do Airflow 4.1 Crie as pastas do Airflow (airflow > dags, logs e plugins) 4.2 Crie o docker-compose.yml e use a doc (https://airflow.apache.org/docs/apache-airflow/2.3.0/start/docker.html) 4.3 No terminal vá até a pasta do airflow 4.4 Rode o comando docker-compose up airflow-init 4.5 Abra um novo terminal e rode docker-compose up 4.6 Acesse localhost:8080
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Instalação do Meltano 5.1 Criar a pasta do Meltano 5.2 Seguir a recomendação da documentação (https://docs.meltano.com/guide/installation-guide) 5.3 Rodar o comando docker pull meltano/meltano 5.4 Inicializar o projeto com cd /your/projects/directory docker run -v "$(pwd)":/projects
-w /projects
meltano/meltano init yourprojectname 5.5 cd yourprojectname
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